Abstract
Neural Machine Translation (NMT) has been proven to achieve impressive results. The NMT system translation results depend strongly on the size and quality of parallel corpora. Nevertheless, for many language pairs, no rich-resource parallel corpora exist. As described in this paper, we propose a corpus augmentation method by segmenting long sentences in a corpus using back-translation and generating pseudo-parallel sentence pairs. The experiment results of the Japanese-Chinese and Chinese-Japanese translation with Japanese-Chinese scientific paper excerpt corpus (ASPEC-JC) show that the method improves translation performance.
Abstract (translated)
神经机器翻译（NMT）已被证明能够取得令人印象深刻的结果。NMT系统的翻译结果很大程度上取决于平行语料库的大小和质量。然而，对于许多语言对来说，并不存在丰富的资源并行语料库。如本文所述，我们提出了一种语料库扩充方法，即使用反向翻译对语料库中的长句子进行分段，并生成伪并行句子对。对日汉科技论文摘要语料库（ASPEC-JC）中日翻译的实验结果表明，该方法提高了翻译效果。
URL
https://arxiv.org/abs/1905.08945
